In this first worldwide synthesis of in situ and satellite‐derived lake data, we find that lake summer surface water temperatures rose rapidly (global mean = 0.34°C decade−1) between 1985 and 2009. Our analyses show that surface water warming rates are dependent on combinations of climate and local characteristics, rather than just lake location, leading to the counterintuitive result that regional consistency in lake warming is the exception, rather than the rule. The most rapidly warming lakes are widely geographically distributed, and their warming is associated with interactions among different climatic factors—from seasonally ice‐covered lakes in areas where temperature and solar radiation are increasing while cloud cover is diminishing (0.72°C decade−1) to ice‐free lakes experiencing increases in air temperature and solar radiation (0.53°C decade−1). The pervasive and rapid warming observed here signals the urgent need to incorporate climate impacts into vulnerability assessments and adaptation efforts for lakes.

Global environmental change has influenced lake surface temperatures, a key driver of ecosystem structure and function. Recent studies have suggested significant warming of water temperatures in individual lakes across many different regions around the world. However, the spatial and temporal coherence associated with the magnitude of these trends remains unclear. Thus, a global data set of water temperature is required to understand and synthesize global, long-term trends in surface water temperatures of inland bodies of water. We assembled a database of summer lake surface temperatures for 291 lakes collected in situ and/or by satellites for the period 1985–2009. In addition, corresponding climatic drivers (air temperatures, solar radiation, and cloud cover) and geomorphometric characteristics (latitude, longitude, elevation, lake surface area, maximum depth, mean depth, and volume) that influence lake surface temperatures were compiled for each lake. This unique dataset offers an invaluable baseline perspective on global-scale lake thermal conditions as environmental change continues.

Here we document the regional effects of Tropical Cyclone Irene on thermal structure and ecosystem metabolism in nine lakes and reservoirs in northeastern North America using a network of high-frequency, in situ, automated sensors. Thermal stability declined within hours in all systems following passage of Irene, and the magnitude of change was related to the volume of water falling on the lake and catchment relative to lake volume. Across systems, temperature change predicted the change in primary production, but changes in mixed-layer thickness did not affect metabolism. Instead, respiration became a driver of ecosystem metabolism that was decoupled from in-lake primary production, likely due to addition of terrestrially derived carbon. Regionally, energetic disturbance of thermal structure was shorter-lived than disturbance from inflows of terrestrial materials. Given predicted regional increases in intense rain events with climate change, the magnitude and longevity of ecological impacts of these storms will be greater in systems with large catchments relative to lake volume, particularly when significant material is available for transport from the catchment. This case illustrates the power of automated sensor networks and associated human networks in assessing both system response and the characteristics that mediate physical and ecological responses to extreme events.

Highlights  The General Lake Model (GLM) is stress tested against 32 globally distributed lakes.  There was low correlation between input data uncertainty and model performance.  Model performance related to lake-morphometry, light extinction and flow regime; deep, clear lakes with high residence times had the lowest model error.

The physical dynamics of lake temperature and ice phenology are important in the modelling and management of temperate aquatic ecosystems. One-dimensional hydrothermal lake models have not been well evaluated in terms of how they simulate ice dynamics in particular. We chose four models (Hostetler, Minlake, Simple Ice Model or SIM and General Lake Model) to test and compare their performance modelling water temperature and ice dynamics using 16 years of field data from Harp Lake, an extensively studied inland lake in south-central Ontario. Each model produced satisfactory water temperature profiles over the simulated period, with small differences in the model performance. Model fits for ice phenology and ice thickness were, however, considerably lower than those for water temperature, with Minlake generating the best agreement with observed ice-on and ice-off dates as well as ice thickness, followed by SIM. The responses of lake ice dynamics to future climate scenarios were simulated by running each of the four models for 91 years, from 2010 to 2100. The predicted decrease in ice season length was significantly different among models, varying between 30 and 81 days, with an average of 48 days. Corresponding decreases in ice thickness varied between 0.11 and 0.20 m, averaging 0.17 m. This study demonstrates that uncertainty due to model performance and selection is considerable, and further testing and refinement of hydrothermal lake dynamic models are needed to improve predictive abilities for ice dynamics. Figure 7. Ice phenology (modelled versus observed) for four models: Hostetler (a), Minlake (b), GLM (c) and SIM (d), in terms of three ice features: ice thickness (i), ice-on date (ii) and ice-off date (iii) 4597 COMPARING ICE AND TEMPERATURE SIMULATIONS BY LAKE MODELS